伪彩色红外图像的小波自适应去噪算法

Adaptive Wavelet Denoising Algorithm for Pseudo-color Infrared Images

针对噪声污染的伪彩色红外图像,提出了一种小波自适应去噪算法。该方法首先将图像分解为R,G,B颜色分量图像,对每幅图像进行小波变换。根据变换后的不同细节子图的小波系数在区域及方向上具有的不同相关性,用不同的窗口对不同细节图像系数的方差进行估计,然后对小波系数进行一种改进的阈值处理,得到结果图像。结果表明,该方法能有效去除噪声,同时较好地保持了图像的边缘和细节。

An adaptive pseudo-color infrared images. pseudo-color infrared images wavelet denoising algorithm presented for noise removal of First, this method separates R, G, and B components from and executes wavelet transform on them. According to different relativities of different detail subimages in region and direction, this method estimates wavelet coefficients＂ variances by using different window in different detail subimages. Then the wavelet coefficients are processed and reconstructed by an improved threshold. The experiment result indicates that the algorithm can maintain the details of the pseudo-color infrared images while removing the noise effectively.